Annotation is the process of adding metadata to some target data. Annotation systems allow users to record insights or notes about any target data for the benefit of future users who view or use the target data. The target data (document) can be any form of data including for example text data, image data, bitmap data, audio data, video data and the like. Annotation systems use computers to simulate the paradigm of ‘sticky-notes’ or ‘margin notes’ that people often use when working with paper documents. People record their judgments and observations about the paper document by marking on the document itself. Thus, when another reader looks at the document, the note is immediately apparent to the reader. Computer Annotation Systems exist to apply this paradigm to electronic target data and documents. Electronic “sticky notes” are annotations applied preferably to a location of the document. Such annotation systems have other advantages as well. Many annotation systems allow for querying the library of annotations and target data as a way to find important judgments or important target documents. Other systems even allow for annotations to perform a workflow task, such as in the system described by Ser. No. 10/983,820 “Multi-User Multi-Timed Collaborative Annotations” Filed Nov. 8, 2004. Many annotation systems also provide the capability of automated annotations, that is, annotations made without user input, usually by batch processes. Annotation systems are in high demand in life sciences industries but are not limited to that domain.
The main problem with current annotation systems is the burden placed on users to create annotations. Users often see annotating a document as having no immediate benefit to the task they are accomplishing. They are often annotating for the vague ideal that it will help another user in the future. While automated annotations remove the user from the process, such annotations are not always appropriate as human insights are often beneficial or required when creating annotations. Annotations also often serve as a tool for adding order to existing freeform data as well and bringing out important data from freeform data. By annotating, the user is often placing the important aspects of some target data into a more structured and queryable form. However users often see such annotation tasks as a bother. The main problems in many annotation systems are often not technical problems but simply that users fail to annotate effectively and thus the usefulness of the annotation system suffers. Thus there is room for improvement upon current annotation systems to make creating annotations have immediate reward for the user and to eliminate annotation tasks that users consider rote, boring, or burdensome.